Summary
You've learned about another type of neural network—a Convolutional Neural Network.
We established that this network is used mostly with images and searches for certain features in these pictures. It uses three additional steps that ANNs don't have: convolution, where we search for features; max pooling, where we shrink the image in size; and flattening, where we flatten 2D images to a 1D vector so that we can input it into a neural network.
In the next chapter, you’ll build a deep convolutional Q-learning model to solve a classic gaming problem: Snake.